Senior AI/ML Engineer

It’s not just about the tech; it’s about the people!

At Career TEAM we work to “accelerate the human condition.” Working on our state-of-the-edge portal Career EDGE, you will change lives and that’s just the beginning! You will be working with new technologies on enterprise products that serve a diverse population across the U.S. You will truly be a full-stack engineer and be able to learn and grow at a faster pace than you can imagine. As a founding member of our newly forming team, you will grow and shape the team as we adeptly traverse this complicated digital landscape of generative AI.

To be considered for this role, you must presently reside in the Philippines.

Specifically, what you will do:

You will help build our AI platform using MongoDB and Nest.js. On any given day, you’ll be coding (writing, reviewing, testing, deploying) because hands-on development is at the heart of what we do. You’ll participate in regular Scrum ceremonies and work closely with the team to integrate AI capabilities (including LLMs, agents, and vector search) seamlessly into our application. You’ll also help define our AI best practices and governance frameworks to ensure our AI usage is both effective and ethical. Innovation is our lifeblood, and you’ll have the opportunity to shape our platform’s direction and experiment with new ideas.

Ideal Candidate Qualifications:

• Bachelor’s degree (or equivalent) in computer science, information technology, or engineering;
• 5+ years of experience developing with TypeScript stack or equivalent;
• 2+ years of experience productionizing LLMs for RAG, Agents, and Multi-Modal Systems.
• Strong analytical & problem-solving skills, effective collaboration & communication skills;
• Experience with LLM agents, fine-tuning, multi-modal models, and prompt engineering;
• Commitment to ethical AI practices and compliance with AI governance standards;
• Solid foundation in AI theory and foundational concepts, such as basic linear algebra concepts (vectors, vector spaces), dimensionality reduction techniques, and model evaluation methods.
• Familiarity with the computational complexity of vector search, tokenization, embedding generation, and large-scale model inference.
• Exposure to VSCode, Postman, GitHub, Vector Databases, and Docker;
• Exposure to building end-to-end systems optimized for speed and scale;
• Exposure to React/Next, Express/Nest, MongoDB, NodeJS, and TypeScript;
• Exposure to developing & deploying RESTful APIs.